2540 Data Science Jobs - Page 45

Bachelors degree in Human Resources, Business Administration, or a related field At least 2 -5 years of experience in IT recruitment, preferably in a fast-paced, technology-driven environment. Proven track record of full-cycle recruitment management, including sourcing, interviewing, and hiring candidates Experience recruiting for IT roles such as software development, infrastructure, data science, and other technology functions Demonstrated ability to leverage social media and other sourcing tools to attract exceptional candidates Excellent communication and interpersonal skills, with the ability to work both independently and collaboratively A passion for staying up-to-date with current and emerging recruitment trends, and a commitment to continuous learning and development Experience with ATS, Microsoft Office suite, and other relevant recruitment tools Familiarity with HR policies, procedures, and employment laws

Exp in leveraging Graph data science concepts to solve business use cases a must. Exp with any graph tools/packages like Neo4J, MemGraph, NetworkX, GraphFrame, iGraph SQL, Python, Scala, ETL frameworks, data warehousing) Required Candidate profile Immediate Joiners

Responsibilities Job Title: Lead Analyst - Data Science (Intermediate/Senior)Role Summary: We are looking for candidates to build and implement analytics solutions to our esteemed clients. The incumbent should have strong aptitude for numbers, experience in any domain and willingness to learn some cutting edge technologies Technical and Professional Requirements: Other key to have Skills: SQL knowledge and experience working with relational databases. Understanding of any one of domain (Eg: Retail, Supply chain, Logistics, Manufacturing). Understanding of the project lifecycles: waterfall and agile. Soft Skills: Strong verbal and written communication skills with the ability to work well in a team. Strong customer focus, ownership, urgency and drive. Ability to handle multiple, competing priorities in a fast-paced environment. Work well with the team members to maintain high credibility Work Experience: Overall 6-8 of years of experience in Data Analytics, Data Science and Machine Learning. Educational Requirements (any of the following): Bachelor of Engineering/Bachelor of Technology in any stream with consistent academic track record. Bachelor's degree in a quantitative discipline (e.g., Statistics, Economics, Mathematics, Marketing Analytics) or significant relevant coursework with consistent academic track record. Preferred Skills: Technology->Data Science->Machine Learning Additional Responsibilities: Additional Academic Qualification (good to have): Masters in any area related to Science, Mathematics, Statistics, Economy and Finance with consistent academic track record. PhD in any stream.Location: Bangalore, Pune, Hyderabad, Chennai, Trivandrum, Mysore Educational Requirements MCA,MSc,Bachelor of Engineering,BBA,BCom Service Line Data & Analytics Unit * Location of posting is subject to business requirements

Position: Data Scientist Trainer Generative AI and Machine Learning Job Location: Chennai/ Bangalore/Noida MODE OF HIRING- TP (THIRD PARTY PAYROLL) CANDIDATE SHOULD BE COMFORTABLE TO TRAVEL INTERNATIONAL/DOMESTIC We are seeking a highly skilled and experienced Data Science and Machine Learning specialist to join our team. The ideal candidate will have a total of 5 to 8 years of professional experience, with a minimum of 2 to 5 years of relevant experience in working with large language models and advanced generative AI algorithms. Responsibilities: 1. Design and implement state-of-the-art machine learning pipelines and processes for data collection, data preprocessing, feature extraction, model training, and model evaluation. 2. Collaborate with cross-functional teams, including software engineers, product managers, and domain experts, to identify and define project requirements and deliverables. 3. Conduct advanced statistical analysis and modeling to gain valuable insights from large-scale datasets and provide actionable recommendations to stakeholders. 4. Explore and experiment with novel approaches and techniques in the field of natural language processing (NLP) and machine learning to improve the performance and capabilities of our language models. 5. Stay up-to-date with the latest research and advancements in the field of NLP and AI, and integrate relevant findings into our research and development efforts. 6. Mentor and coach junior members of the team, fostering a culture of learning, knowledge sharing, and professional growth. 7. Assist in the development and implementation of best practices, coding standards, and quality assurance processes. Requirements: 1. Bachelor's or Master's degree in Computer Science, Data Science, or a related field. PhD preferred. 2. Strong expertise in machine learning, deep learning, and natural language processing, with a focus on large language models and generative AI. 3. Extensive hands-on experience with machine learning frameworks and libraries, such as TensorFlow, PyTorch, or Keras. 4. Proficiency in programming languages like Python, R, or Java for data manipulation, analysis, and model development. 5. Solid understanding of statistics, probability theory, and mathematical optimization. 6. Proven track record of successfully leading and managing data science and machine learning projects from conception to delivery. 7. Excellent problem-solving skills with the ability to think critically and analytically. 8. Strong written and verbal communication skills, with the ability to effectively present complex concepts and findings to both technical and non-technical stakeholders. If you are passionate about pushing the boundaries of language models and generative AI, and you have a strong background in data science and machine learning, we encourage you to apply. Join our team and contribute to advancing the state-of-the-art in AI!

About the Opportunity Job TypeApplication 21 June 2025 Title Senior Analyst- Data Scientist Department Data Value Location Gurgaon Reports To Suman Kaur Level 3 Were proud to have been helping our clients build better financial futures for over 50 years. How have we achieved thisBy working together - and supporting each other - all over the world. So, join our Data Value team and feel like youre part of something bigger. About your team Data Value team drives the renewed focus of extracting value from Fidelitys data for business and client insights and working as one voice with the business, technology, and data teams. The teams vision is to create measurable business impact by leveraging technology and utilising the skills to generate valuable insights and streamline engagements. The Data Science function within Data Value supports Fidelity Internationals Sales, Marketing, Propositions, Risk, Finance, Customer Service and HR teams across the globe. The key objectives of the function are: To develop deep customer insights for our businesses helping them segment and target customers more effectively To develop a fact-based understanding of sales trends and identify actionable sales growth opportunities for each of our sales channels To understand customer preferences in terms of products, service attributes and marketing activity to help refine each of these To help develop new services lines e.g. develop customer analytics for key IFAs, DC Clients, Individual clients etc. To develop market and competitive intelligence in our key markets to help shape our business planning in those markets The function works directly with business heads and other senior stakeholders stakeholders to identify areas of analytics, define problem statements and develop key insights. About your role You will be expected to take a leading role in developing the Data Science and Advanced Analytics solutions for our business. This will involve: Engaging with the key stakeholders to understand Fidelitys sales, marketing, client services and propositions context Implement advanced analytics solutions on On-Premises/Cloud platforms, develop proof-of-concepts and engage with internal and external ecosystem to progress the proof of concepts to production. Engaging and collaborating with different other internal teams like Data engineering, DevOps, technology team etc for development of new tools, capabilities, and solutions. Maximize Adoption of Cloud Based advanced analytics solutionsBuild out sandbox analytics environments using Snowflake, AWS, Adobe, Salesforce. About you Key Responsibilities Developing and Delivering Data Science solutions for business (40%) Partner with internal (FIL teams) & external ecosystem to design and deliver advanced analytics enabled Data Science solutions Create advanced analytics solution on quantitative and text data using Artificial Intelligence, Machine Learning and NLP techniques. Create compelling visualisations that enable the smooth consumption of predictions and insights for customer benefit . Stakeholder Management (30%) Works with channel heads/stakeholders and other sponsors understand the business problem and translate it into appropriate analytics solution. Engages with key stakeholders for smooth execution, delivery, and implementation of solutions Adoption of Cloud enabled Data Science solutions(20%) Maximize Adoption of Cloud Based advanced analytics solution Build out sandbox analytics environments using Snowflake, AWS, Adobe, Salesforce Deploy solutions in productions while adhering to best practices involving Model Explainability, MLOps, Feature Stores, Model Management, Responsible AI etc Collaboration and Ownership (10%) Sharing of knowledge, best practices with the team including coaching or training in some of deep learning/machine learning methodologies. Provides mentoring, coaching, and consulting advice and guidance to staff, e.g. analytic methodologies, data recommendations Takes complete independent ownership of the projects and the initiatives in the team with the minimal support Experience and Qualifications Required Qualifications: Engineer from IIT/Masters in field related to Data Science/Economics/Mathematics (Tie1 Institutions like ISI, Delhi School of Economics)/M.B.A from tier 1 institutions Must have Skills & Experience Required: Overall, 8+ years of experience in Data Science and Analytics 5+ years of hands-on experience in - Statistical Modelling /Machine Learning Techniques/Natural Language Processing/Deep Learning 5+ years of experience in Python/Machine Learning/Deep Learning Excellent problem-solving skills Should be able to run analytics applications such as Python, SAS and interpret statistical results Implementation of models with clear measurable outcomes Good to have Skills & Experience Required: Ability to engage in discussion with senior stakeholders on defining business problems, designing analyses projects, and articulating analytical insights to stakeholders. Experience on SPARK/Hadoop/Big Data Platforms is a plus Experience with unstructured data and big data Experience with secondary data and knowledge of primary market research is a plus. Ability to independently own and manage the projects with minimal support. Excellent analytical skills and a strong sense for structure and logic Ability to develop, test and validate hypotheses. Feel rewarded For starters, well offer you a comprehensive benefits package. Well value your wellbeing and support your development. And well be as flexible as we can about where and when you work finding a balance that works for all of us. Its all part of our commitment to making you feel motivated by the work you do and happy to be part of our team. For more about our work, our approach to dynamic working and how you could build your future here, visit careers.fidelityinternational.com.

About the Opportunity Job TypeApplication 20 June 2025 Title Data Scientist, Risk Data Analytics Department Data Value Location Gurgaon Reports To Associate Director, Risk Data Analytics Level 5 Were proud to have been helping our clients build better financial futures for over 50 years. How have we achieved thisBy working together - and supporting each other - all over the world. So, join our Data Value team and feel like youre part of something bigger. About Global Risk The Global Risk team in Fidelity covers the management oversight of Fidelitys risk profile, including key risk frameworks, policies and procedures and oversight and challenge processes. The team partner with the businesses to ensure Fidelity manages its risk profile within defined risk appetite. The team comprises risk specialists covering all facets of risk management, including investment, financial, non-financial and strategic risk. As part of a broader General Counsel team, the Risk team collaborates closely with Compliance, Legal, Tax and Corporate Sustainability colleagues. About Risk Data Analytics Hub The vision of Risk Data Analytics Hub is to establish a data-centric risk function that is forward-thinking, resilient, and proactive. The hubs mission is to enhance risk management processes and unlock innovative opportunities in the ever-changing risk and business landscape. The Hub has made significant strides in the Investment Risk, delivering prominent contributions such as the Fund Performance Monitoring, Fund Aggregate Exposures, Fund Market Risk, Fund Liquidity Risk, and other comprehensive monitoring and reporting dashboards. These tools have been crucial in supporting risk oversight and regulatory submissions. The Hubs goal is to scale this capability across global risk, using data-driven insights to uncover hidden patterns and predict emerging risks. This will enable decision-makers to prioritise actions that align with business objectives. The approach is to dismantle silos and foster collaboration across the global risk team, introducing new tools, techniques, and innovation themes to enhance agility. About your role You will be expected to take a leading role in developing the Data Science and Advanced Analytics solutions for our business. This will involve: Engaging with the key stakeholders to understand various subject areas in Global Risk Team including Investment Risk, Non-Financial Risk, Enterprise Risk, Model Risk, Enterprise Resilience etc. Implement advanced analytics solutions on On-Premises/Cloud platforms, develop proof-of-concepts and engage with internal and external ecosystem to progress the proof of concepts to production. Engaging and collaborating with different other internal teams like Data Lake, Data Engineering, DevOps/MLOps, Technology team etc for development of new tools, capabilities, and solutions. Maximize adoption of Cloud Based advanced analytics solutionsBuild out sandbox analytics environments using Snowflake, AWS, Adobe, Salesforce. Support delivered models and infrastructure on AWS including data changes and model tuning About you Key Responsibilities Developing and Delivering Data Science solutions for business (40%) Partner with internal (FIL teams) & external ecosystem to design and deliver advanced analytics enabled Data Science solutions. Create advanced analytics solution on quantitative and text data using Artificial Intelligence, Machine Learning and NLP techniques. Create compelling visualisations that enable the smooth consumption of predictions and insights for customer benefit. . Stakeholder Management (30%) Works with Risk SMEs/Managers, stakeholders and sponsors to understand the business problem and translate it into appropriate analytics solution. Engages with key stakeholders for smooth execution, delivery, implementation and maintenance of solutions. Adoption of Cloud enabled Data Science solutions(20%) Maximize Adoption of Cloud Based advanced analytics solution Build out sandbox analytics environments using Snowflake, AWS, Adobe, Salesforce Deploy solutions in productions while adhering to best practices involving Model Explainability, MLOps, Feature Stores, Model Management, Responsible AI etc Collaboration and Ownership (10%) Sharing of knowledge, best practices with the team including coaching or training in some of deep learning/ machine learning methodologies. Provides mentoring, coaching, and consulting advice and guidance to staff, e.g. analytic methodologies, data recommendations. Takes complete independent ownership of the projects and the initiatives in the team with the minimal support. Experience and Qualifications Required Qualifications: Engineer from IIT/Masters in field related to Data Science/Economics/Mathematics (Tie1 Institutions like ISI, Delhi School of Economics)/M.B.A from tier 1 institutions Must have Skills & Experience Required: Overall, 9+ years of experience in Data Science and Analytics 5+ years of hands-on experience in - Statistical Modelling /Machine Learning Techniques/Natural Language Processing/Deep Learning 5+ years of experience in Python/Machine Learning/Deep Learning Excellent problem-solving skills Should be able to run analytics applications such as Python, SAS and interpret statistical results Implementation of models with clear measurable outcomes Good to have Skills & Experience Required: Ability to engage in discussion with senior stakeholders on defining business problems, designing analyses projects, and articulating analytical insights to stakeholders. Experience on SPARK/Hadoop/Big Data Platforms is a plus. Experience with unstructured data and big data. Experience with secondary data and knowledge of primary market research is a plus. Ability to independently own and manage the projects with minimal support. Excellent analytical skills and a strong sense for structure and logic. Ability to develop, test and validate hypotheses.

Responsibilities Responsibilities:- Assess the complete ML development process.- Data Engineering- Evaluate the maturity level of ML systems. - Software Development- Provide recommendations for improvement - DevOps- Implement and maintain CI/CD pipelines for ML models. - Monitor and manage model performance in production. Technical and Professional Requirements: - 3+ years in MLOps or related roles - Data Science- Hands-on experience with ML model deployment and monitoring - System Administration- Proven track record of implementing CI/CD pipelines - Automation Tools- Experience with version control systems (Git). Preferred Skills: Technology->Machine Learning->MLOps Educational Requirements Bachelor of Engineering Service Line Quality * Location of posting is subject to business requirements

QualificationBE or BTech/Mtech only Data science certification from any prestigious institutes. Exp Works in the area of Software Engineering, which encompasses the development, maintenance and optimization of software solutions/applications. 1. Applies scientific methods to analyse and solve software engineering problems. 2. He/she is responsible for the development and application of software engineering practice and knowledge, in research, design, development and maintenance. 3. His/her work requires the exercise of original thought and judgement and the ability to supervise the technical and administrative work of other software engineers. 4. The software engineer builds skills and expertise of his/her software engineering discipline to reach standard software engineer skills expectations for the applicable role, as defined in Professional Communities. 5. The software engineer collaborates and acts as team player with other software engineers and stakeholders. Works in the area of Software Engineering, which encompasses the development, maintenance and optimization of software solutions/applications.1. Applies scientific methods to analyse and solve software engineering problems.2. He/she is responsible for the development and application of software engineering practice and knowledge, in research, design, development and maintenance.3. His/her work requires the exercise of original thought and judgement and the ability to supervise the technical and administrative work of other software engineers.4. The software engineer builds skills and expertise of his/her software engineering discipline to reach standard software engineer skills expectations for the applicable role, as defined in Professional Communities.5. The software engineer collaborates and acts as team player with other software engineers and stakeholders. - Grade Specific Is fully competent in it's own area and has a deep understanding of related programming concepts software design and software development principles. Works autonomously with minimal supervision. Able to act as a key contributor in a complex environment, lead the activities of a team for software design and software development. Acts proactively to understand internal/external client needs and offers advice even when not asked. Able to assess and adapt to project issues, formulate innovative solutions, work under pressure and drive team to succeed against its technical and commercial goals. Aware of profitability needs and may manage costs for specific project/work area. Explains difficult concepts to a variety of audiences to ensure meaning is understood. Motivates other team members and creates informal networks with key contacts outside own area. Skills (competencies) Verbal Communication

Capgemini Invent Capgemini Invent is the digital innovation, consulting and transformation brand of the Capgemini Group, a global business line that combines market leading expertise in strategy, technology, data science and creative design, to help CxOs envision and build whats next for their businesses. Your role Predictive and Prescriptive modelling using Statistical and Machine Learning algorithms including but not limited to Time Series, Regression, Trees, Ensembles, Neural-Nets (Deep & Shallow CNN, LSTM, Transformers etc.). Experience with open-source OCR engines like Tesseract, Speech recognition, Computer Vision, face recognition, emotion detection etc. is a plus. Unsupervised learning Market Basket Analysis, Collaborative Filtering, Dimensionality Reduction, good understanding of common matrix decomposition approaches like SVD. Various Clustering approaches Hierarchical, Centroid-based, Density-based, Distribution-based, Graph-based clustering like Spectral. NLP Information Extraction, Similarity Matching, Sentiment Analysis, Text Clustering, Semantic Analysis, Document Summarization, Context Mapping/Understanding, Intent Classification, Word Embeddings, Vector Space Models, experience with libraries like NLTK, Spacy, Stanford Core-NLP is a plus. Usage of Transformers for NLP and experience with LLMs like (ChatGPT, Llama) and usage of RAGs (vector stores like LangChain & LangGraps), building Agentic AI applications. Graph Analytics Familiarity with Graph Algorithms (Directed & Undirected) Traversal (BFS, DFS), Cycle Detection (Bellman Ford, Flyod Warshall), Shortest Path (Dijkstra, A*) etc. Building Knowledge Graphs with unstructured data and knowledge graph optimizations like PageRank/TrustRank is expected Mathematical Optimization Familiarity with common optimization algorithms, both discrete Linear, Mixed-Integer, Goal, Dynamic etc and continuous GD and its variants, Newtons method etc. is expected. Experience with Simulated Annealing and exposure to ML inspired evolutionary optimization algorithms like Genetic Algorithm & Genetic Programming for optimization is a plus. Simulations Monte Carlo Simulation, Discrete-Event Simulation, Agent-Based Simulation, Hybrid Simulation, System Dynamics, Genetic Algorithm based Simulation. Model Deployment ML pipeline formation, data security and scrutiny check and ML-Ops for productionizing a built model on-premises and on cloud. Your Profile Programming Languages Python NumPy, SciPy, Pandas, MatPlotLib, Seaborne Databases RDBMS (MySQL, Oracle etc.), NoSQL Stores (HBase, Cassandra etc.) ML/DL Frameworks SciKitLearn, TensorFlow (Keras), PyTorch, Big data ML Frameworks - Spark (Spark-ML, Graph-X), H2O Cloud Azure/AWS/GCP Experienced in Agile way of working, manage team effort and track through JIRA Experience in Proposal, RFP, RFQ and pitch creations and delivery to the big forum. Experience in POC, MVP, PoV and assets creations with innovative use cases Experience working in a consulting environment is highly desirable. What you will love about working here We recognize the significance of flexible work arrangements to provide support. Be it remote work, or flexible work hours, you will get an environment to maintain healthy work life balance. At the heart of our mission is your career growth. Our array of career growth programs and diverse professions are crafted to support you in exploring a world of opportunities. Equip yourself with valuable certifications in the latest technologies such as Generative AI. About Capgemini Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, cloud and data, combined with its deep industry expertise and partner ecosystem. The Group reported 2023 global revenues of 22.5 billion.

REF69967Q_2025151745 - Deputy Manager - Operations - Data science Roles & Responsibilities: Data Analysis: Analyse large datasets to extract meaningful insights and trends Model Development: Develop and implement predictive models and machine learning algorithms to solve business problems Data Cleaning: Ensure data quality by cleaning and pre-processing data Visualization: Create visualizations to present data insights using tools like Power BI or Python libraries (eg, Matplotlib, Seaborn) Collaboration: Work closely with data engineers, software developers, and business stakeholders to understand requirements and deliver solutions Reporting: Generate automated reports and dashboards to provide actionable insights Research: Stay updated with the latest trends and technologies in data science and machine learning Technical Skills Required: Programming Languages: Proficiency in Python and SQL Machine Learning: Experience with machine learning frameworks such as Scikit-learn, TensorFlow, or PyTorch Data Visualization: Skills in data visualization tools like Power BI, Matplotlib, Seaborn, or Plotly Statistical Analysis: Strong understanding of statistical methods and techniques Data Wrangling: Expertise in data wrangling and pre-processing using libraries like Pandas and NumPy Platforms like Power BI, Power Automate, Apps are good to have

We are looking for an experienced Analytics Engineer to join Okta s enterprise data team. This analyst will have strong background in SaaS subscription and product analytics, a passion for providing customer usage insights to internal stakeholders, and experience organizing complex data into consumable data assets. In this role, you will be focusing on subscription analytics and product utilization insights and will partner with Product, Engineering, Customer Success, and Pricing to implement enhancements and build end-to-end customer subscription insights into new products. Requirements Experience in customer analytics, product analytics, and go-to-market analytics Experience in SaaS business, Product domain as well as Salesforce Proficiency in SQL, ETL tools, GitHub, and data integration technologies, including familiarity with data modeling techniques, database design, and query optimization. Experience in data languages like R and Python. Knowledge of data processing frameworks like PySpark is also beneficial. Experience working with cloud-based data solutions like AWS or Google Cloud Platform and cloud-based data warehousing tools like Snowflake. Strong analytical and problem-solving skills to understand complex data problems and provide effective solutions. Experience in building reports and visualizations to represent data in Tableau or Looker Ability to effectively communicate with stakeholders, and work cross-functionally and communicate with technical and non-technical teams Familiarity with SCRUM operating model and tracking work via a tool such as Jira 6+ years in data engineering, data warehousing, or business intelligence BS in computer science, data science, statistics, mathematics, or a related field Responsibilities Engage with Product and Engineering to implement product definitions into subscription and product analytics, building new insights and updates to existing key data products Analyze a variety of data sources, structures, and metadata and develop mapping, transformation rules, aggregations and ETL specifications Configure scalable and reliable data pipelines to consume, integrate and analyze large volumes of complex data from different sources to support the growing needs of subscription and product analytics Partner with internal stakeholders to understand user needs and implement user feedback, and develop reporting and dashboards focused on subscription analytics Work closely with other Analytics team members to optimize data self service, reusability, performance, and ensure validity of source of truth Enhance reusable knowledge of the models and metrics through documentation and use of the data catalog Ensure data security and compliance by implementing appropriate data access controls, encryption, and auditing mechanisms. Take ownership of successful completion for project activities Nice to Have Experience in data science, AI/ML concepts and techniques.

At (TekLink HGS Digital), our vision is to be the globally preferred digital transformation partner for our clients, creating value in their business through rigorous innovation at scale. We are an expert team of 500+ leading strategic thinkers, digital marketing and creative masters, data analysts, software engineers, and process optimization specialists with an elemental desire to create transformative digital solutions. Job Title: Data Scientist Location: Hyderabad, India Duration: Full time . Data scientist would support our internal teams and clients in driving strategic decisions, applying advanced statistical & predictive analytics and machine learning concepts to solve business problems in BFSI and CPG domains. You will also phrase requirements document, contribute towards project plan, carry out data research and collection, study attributes and features, test for parameters, resolve data issues, decide on models, modeling, QA/testing and showcase the findings in various formats for client consumption. Responsibilities: a) Analytics Requirements Definition: Works with business users to approve the requirements for analytics solution. b) Data Preparation: Reviews data preparation rules (data extraction, data integration, data granularity, data cleansing etc.). Prepares data for analytical modelling. Guides data analysts and associate data scientists on data preparation activities. c) Builds Machine Learning (ML) and Statistical Models using Python/R/Scala/SAS/SPSS d) Collaborate with clients and internal teams to define industry-leading analytics solutions for a wide variety of industries and business groups e) Develop proof-of-concepts and demos needed for client & internal presentations f) Create clear functional and technical documentation g) Work agnostic across multiple industry sectors and functional domains, with focus on BFSI and CPG domains. h) Work closely with all stakeholders to identify, evaluate, design, and implement statistical and other quantitative approaches for modeling enterprise scale data and big data i) Display proficiency in converting algorithmic proof of concepts into business requirement documents for product development or data driven actionable intelligence Minimum Requirements & Qualification The ideal candidate should have: Full time Degree in Mathematics, Statistics, Computer Science or Computer Applications from reputed institutions, B.E./B.Tech., MBA specialized in Marketing, Operations Research, Data Science and/or Business Analytics Overall 8+ years of technical experience in IT industry across BFSI and CPG domains. Minimum of 5 years of hands-on work experience in Data Science/Advance analytics, Machine Learning using Python and SQL Practical experience specifically around quantitative and analytical skills is required. People management skills and experience, and familiarity with the pharmaceutical industry are preferred. Knowledge of solution design, planning, and execution Contribute to case studies, blogs, eBooks, and whitepapers Proficiency in maintaining strong project documentation hygiene Able to fully assimilate into automated MLOps mode Must have good communication skills written, oral, ppt and language skills Able to translate statistical findings to business English Hands on experience in one or more of the skillsets below: Programming Language: R Programming, Base SAS, Advanced SAS Visualization Tool: Tableau, MS Excel, think-cell, Power BI, Qlik Sense Automation Tool: VBA Macro, Python scripts Basic understanding of NLP/NLU/NLG and text mining Skills/knowledge of advanced ML techniques with image processing and signal processing is a plus GenAI and multimodal GenAI skills with RAG development and fine tuning Sounds statistical training in linear and non-linear regression, weighted regression, clustering, and classification techniques Sound understanding of applied statistical methods including survival analysis, categorical data analysis, time series analysis and multivariate statistics Introduction to classical statistical including concepts in Bayesian statistics, experimental design and inference theory Practical understanding of concepts in computer vision, data mining, machine learning, information retrieval, pattern recognition and knowledge discovery Additional knowledge in WFM, biological learning systems and modern statistical concepts is a plus Knowledge of IoT devices and solutions with multi-sensor data fusion is a plus Knowledge of Geostatistics, information theory, computational statistics is a plus Experience in character recognition with image, speech, and video analytics capabilities is a plus Working knowledge of or certifications in AWS/Azure/GCP is beneficial

We are seeking qualified and passionate faculty members to join our Computer Science & Engineering department. The ideal candidate should possess strong academic credentials, a commitment to teaching and research excellence, and the ability to mentor and inspire students in a dynamic learning environment. Role & responsibilities Preferred candidate profile

Job Summary: We are seeking a skilled Data Scientist with experience in both Python and SAS to join our high-performing analytics team. The ideal candidate will be adept at developing predictive models, analyzing large datasets, and delivering actionable insights using modern data science tools and platforms. Key Responsibilities: Design and develop machine learning and statistical models using Python and SAS. Conduct data exploration, preprocessing, and analysis on structured and unstructured datasets. Use SAS (Base, Advanced, Enterprise Guide, Visual Analytics, or SAS Viya) for reporting, data preparation, and statistical modeling as required. Work with large-scale datasets using Python libraries such as Pandas, NumPy, Scikit-learn, and TensorFlow. Translate business requirements into technical solutions in collaboration with cross-functional teams. Build data pipelines and automate workflows for data analysis and model deployment. Present data-driven insights through visualizations using tools such as Seaborn, Plotly, Matplotlib, or SAS VA. Document models, code, and methodologies for reproducibility and auditability. Qualifications: 2-10 years of experience in data science, machine learning, or advanced analytics. Proficient in Python (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, etc.) and SAS (Base, Advanced, DI, VA, or Viya). Strong knowledge of SQL and experience working with relational databases. Solid foundation in statistical analysis, hypothesis testing, regression, classification, clustering, etc. Experience in building, evaluating, and deploying predictive models. Excellent communication skills and ability to convey complex findings to non-technical stakeholders. Preferred Qualifications : Experience with big data tools (Spark, Hive, Hadoop). Exposure to MLOps tools (MLflow, Airflow, Docker, etc.). Familiarity with cloud platforms (AWS, Azure, GCP). Understanding of SAS integration with cloud or open-source tools. Experience with NLP, image recognition, or deep learning frameworks. Location- Pan ,Delhi NCR,Bengaluru,Chennai,Pune,Kolkata,Ahmedabad,Mumbai, Hyderabad Education- Bachelor's degree in Computer Science, Information Technology, or a related field.

We are looking for an AI Engineer with experience in Speech-to-text and Text Generation to solve a Conversational AI challenge for our client based in EMEA. The focus of this project is to transcribe conversations and leverage generative AI-powered text analytics to drive better engagement strategies and decision-making. The ideal candidate will have deep expertise in Speech-to-Text (STT), Natural Language Processing (NLP), Large Language Models (LLMs), and Conversational AI systems. This role involves working on real-time transcription, intent analysis, sentiment analysis, summarization, and decision-support tools. Key Responsibilities 1. Conversational AI & Call Transcription Development Develop and fine-tune automatic speech recognition (ASR) models Implement language model fine-tuning for industry-specific language. Develop speaker diarization techniques to distinguish speakers in multi-speaker conversations. 2. NLP & Generative AI Applications Build summarization models to extract key insights from conversations. Implement Named Entity Recognition (NER) to identify key topics. Apply LLMs for conversation analytics and context-aware recommendations. Design custom RAG (Retrieval-Augmented Generation) pipelines to enrich call summaries with external knowledge. 3. Sentiment Analysis & Decision Support Develop sentiment and intent classification models. Create predictive models that suggest next-best actions based on call content, engagement levels, and historical data. 4. AI Deployment & Scalability Deploy AI models using tools like AWS, GCP, Azure AI, ensuring scalability and real-time processing. Optimize inference pipelines using ONNX, TensorRT, or Triton for cost-effective model serving. Implement MLOps workflows to continuously improve model performance with new call data. Technical Skills Strong experience in Speech-to-Text (ASR), NLP, and Conversational AI. Hands-on expertise with tools like Whisper, DeepSpeech, Kaldi, AWS Transcribe, Google Speech-to-Text. Proficiency in Python, PyTorch, TensorFlow, Hugging Face Transformers. Experience with LLM fine-tuning, RAG-based architectures, and LangChain. Hands-on experience with Vector Databases (FAISS, Pinecone, Weaviate, ChromaDB) for knowledge retrieval. Experience deploying AI models using Docker, Kubernetes, FastAPI, Flask. Soft Skills Ability to translate AI insights into business impact. Strong problem-solving skills and ability to work in a fast-paced AI-first environment. Excellent communication skills to collaborate with cross-functional teams, including data scientists, engineers, and client stakeholders. Preferred Qualifications Experience in healthcare, pharma, or life sciences NLP use cases. Background in knowledge graphs, prompt engineering, and multimodal AI. Experience with Reinforcement Learning (RLHF) for improving conversation models.

We are looking for an AI Engineer with experience in Speech-to-text and Text Generation to solve a Conversational AI challenge for our client based in EMEA. The focus of this project is to transcribe conversations and leverage generative AI-powered text analytics to drive better engagement strategies and decision-making. The ideal candidate will have deep expertise in Speech-to-Text (STT), Natural Language Processing (NLP), Large Language Models (LLMs), and Conversational AI systems. This role involves working on real-time transcription, intent analysis, sentiment analysis, summarization, and decision-support tools. Key Responsibilities: 1. Conversational AI & Call Transcription Development Develop and fine-tune automatic speech recognition (ASR) models Implement language model fine-tuning for industry-specific language. Develop speaker diarization techniques to distinguish speakers in multi-speaker conversations. 2. NLP & Generative AI Applications Build summarization models to extract key insights from conversations. Implement Named Entity Recognition (NER) to identify key topics. Apply LLMs for conversation analytics and context-aware recommendations. Design custom RAG (Retrieval-Augmented Generation) pipelines to enrich call summaries with external knowledge. 3. Sentiment Analysis & Decision Support Develop sentiment and intent classification models. Create predictive models that suggest next-best actions based on call content, engagement levels, and historical data. 4. AI Deployment & Scalability Deploy AI models using tools like AWS, GCP, Azure AI, ensuring scalability and real-time processing. Optimize inference pipelines using ONNX, TensorRT, or Triton for cost-effective model serving. Implement MLOps workflows to continuously improve model performance with new call data. What you will bring to the Table?: Technical Skills 8+ Years of overall experience, Strong expertise in Speech-to-Text (ASR), NLP, and Conversational AI. Hands-on expertise with tools like Whisper, DeepSpeech, Kaldi, AWS Transcribe, Google Speech-to-Text. Proficiency in Python, PyTorch, TensorFlow, Hugging Face Transformers. Experience with LLM fine-tuning, RAG-based architectures, and LangChain. Hands-on experience with Vector Databases (FAISS, Pinecone, Weaviate, ChromaDB) for knowledge retrieval. Experience deploying AI models using Docker, Kubernetes, FastAPI, Flask. Soft Skills Ability to translate AI insights into business impact. Strong problem-solving skills and ability to work in a fast-paced AI-first environment. Excellent communication skills to collaborate with cross-functional teams, including data scientists, engineers, and client stakeholders. Preferred Qualifications Experience in healthcare, pharma, or life sciences NLP use cases. Background in knowledge graphs, prompt engineering, and multimodal AI. Experience with Reinforcement Learning (RLHF) for improving conversation models.

We are looking for a highly skilled and experienced Analyst to join our Data Analytics team at Equitas Small Finance Bank Ltd. The ideal candidate will have 2-5 years of experience in data analysis and analytics, with a strong background in the BFSI industry. Roles and Responsibility Analyze complex data sets to identify trends and patterns that inform business decisions. Develop and maintain databases and data systems to support business intelligence initiatives. Collaborate with cross-functional teams to design and implement data-driven solutions. Provide data-driven insights and recommendations to senior management and stakeholders. Develop and maintain reports and dashboards to track key performance indicators. Stay up-to-date with industry trends and emerging technologies in data analytics. Job Requirements Strong understanding of data analysis and visualization tools such as Excel, SQL, or Tableau. Experience working with large datasets and developing predictive models. Excellent communication and problem-solving skills, with the ability to work effectively in a team environment. Ability to prioritize multiple tasks and deadlines in a fast-paced environment. Strong attention to detail and organizational skills, with the ability to maintain accurate records. Familiarity with regulatory requirements and industry standards in the BFSI sector.

Roles and Responsibilities Design and deliver training programs for corporates on emerging technologies such as AI, ML, DevOps, Data Science, Python, JavaScript, etc. Develop course materials and presentations to effectively communicate complex technical concepts to non-technical audiences. Conduct hands-on sessions and workshops to facilitate learning and knowledge transfer. Collaborate with subject matter experts (SMEs) to develop customized training solutions that meet client requirements. Provide post-training support through coaching, mentoring, or knowledge transfer sessions. Desired Candidate Profile 2-5 years of experience in corporate training or a related field. Strong understanding of artificial intelligence, machine learning algorithms, data science principles, cloud computing platforms (AWS), DevOps practices. Proficiency in programming languages like Python; familiarity with JavaScript is an added advantage. Bachelor's degree in Computers (B.Tech/B.E.) or Electronics/Telecommunication (B.Tech/B.E.).

Key Responsibilities: - Gather and extract data from various databases and sources, ensuring data quality and consistency. - Perform detailed data analysis to uncover trends, patterns, and actionable insights that support business objectives. - Develop predictive models and algorithms to address complex business challenges and forecast outcomes. - Use statistical tools and machine learning techniques to optimize processes and inform strategic initiatives. To provide suggestions and research backed recommendations for adoption of newer tools and available products to enhance data productivity - Design and implement automated dashboards and reporting systems to streamline data insights and accessibility. - Develop automated alert mechanisms to promptly notify relevant stakeholders of significant changes or anomalies. - Collaborate with cross-functional customer experience teams to understand data needs and provide analytical support. - Present findings and recommendations to senior leadership in a clear, concise, and impactful manner. - Lead and manage data science projects from conception to completion, ensuring timely delivery and alignment with organizational goals. - Mentor and guide junior data scientists and analysts, fostering a culture of continuous learning and innovation. Qualifications: - Bachelors or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field. - Experience in data science, analytics, or a similar role, with at least 4-5 years in a leadership or managerial position. - Proven experience in building and deploying machine learning models and automated solutions. Technical Skills: - Proficiency in programming languages such as Python, R, or Java. - Strong SQL skills and experience with data querying and transformation. - Familiarity with big data technologies like Hadoop, Spark, or AWS. - Experience with data visualization tools such as Tableau, Power BI, or similar. - Knowledge of statistical analysis and machine learning frameworks (e.g., scikit-learn, TensorFlow). Soft Skills: - Strong analytical and problem-solving abilities. - Excellent communication and presentation skills, with the ability to convey complex data insights to non-technical stakeholders. - Ability to work collaboratively in a team environment and lead projects with minimal supervision. Preferred Qualifications: - Experience in creating real-time data pipelines and automated alert systems. - Understanding of data governance and compliance practices. - Prior experience in aviation or a customer-centric or high-growth industry is a plus. "At IndiGo, we believe in the innate strength of an energetic, diverse, and inclusive workforce, where the viewpoints and life experiences of our employees help us foster strong connections with all our customers. Our diversity equity and inclusion efforts are designed to attract, nurture, and advance the lives of our employees and customers irrespective of their – but not limited to - gender, race, color, religion, caste, creed, ethnicity, origin, language, social and economic status, sexual orientation, differently-abled status, marital status, nationality, age, family status, and maternity status"

Workdays : Mon to Fri Job Description: The Data Scientist is responsible for contributing to the development of the strategy for Analytics, Reporting and Metrics building in line with overall Business Information Services strategy leveraging visualization tools/business intelligence platforms. Your role will include the following:- Coordinate with different functional teams to implement models and monitor outcomes. Develop processes and tools to monitor and analyze model performance and data accuracy. Leveraging business intelligence tools i.e Spotfire for analysis and review. Develop custom data models and algorithms to apply to data sets. Providing specialist support for development, interpretation and application of machine learning models Applying analytical and statistical methods to solve identified use cases in an agile manner using various data sources and analytical tools Work with key stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions. Liaising, advising and negotiating with key customer groups on requirements and proposing innovative solutions to meet their data modelling requirements Responsible for the development and implementation of capabilities to make provisioning of routine requests more routine, structured and efficient Contributing to initiatives that enable faster and more effective data modelling/analysis and provisioning Ensuring systems and code, documentation are inspection ready What Required: Were looking for someone with 3-5 years of experience manipulating data sets and building statistical models, has a Masters or PHD in Statistics, Mathematics, Computer Science. Experience using statistical computer languages Python & SQL (R Considered) to manipulate data and draw insights from large data sets. Experience working with and creating data architectures. Experience of clinical data and domains (Experience working within Clinical Trials or the wider Pharmaceutical industry) preferable but not necessary Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks. Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications. Excellent written and verbal communication skills for coordinating across teams. A drive to learn and master new technologies and techniques.

Hiring Assistant Professors in Mathematics with Ph.D. and 2–7 years’ experience in teaching and research. Specializations include Linear Algebra, Probability, Optimization, Data Science, and Machine Learning.

Role: Senior Analyst (Retail Analytics) Exp: 3-8 years Work location: Bangalore, Chennai, Hyderabad, Pune, Mumbai, Gurgaon Mandatory Skills: SQL + Python + Tableau or PowerBI or Datorama or Looker Studio + Advanced Excel + Statistical Modelling + Retail Analytics Good to have skills: R, SAS, Deep Learning, Artificial Intelligence Interested candidates can share their profiles with bindu@logicalhiring.com References are welcome! For other open roles, please visit - www.logicalhiring.com

Job Summary We are seeking a skilled Data Scientist to join Digital Finance-Disruptive Tec - Global Finance Services Division. The incumbent would be Performing analytical tasks and initiatives on huge amount of data to support data-driven business decision and development. The preference for this role is to be based out of Whitefield Office, Bangalore, India What you will do Caterpillar uses quantitative methods such as business simulations, data mining, and advanced statistical techniques to solve problems. The Data Scientist contributes to this mission by leveraging his or her quantitative analysis, data management, modeling and/or data visualization skills as an individual contributor to project teams tasked with solving business problems. Caterpillar uses quantitative techniques to solve problems. Typical problems include maximizing Operating Profit After Capital Charge through improvements in Inventory Costs, Material Costs, New Product Introduction costs, etc.; determining the principal drivers of health care costs; recommending the optimal supplier for a part; identifying sales, rental, and service opportunities for Caterpillar dealers; and developing simulation/optimization capabilities to model a new facility or product feature. In addition, analytics experts also provide assistance to high-profile enterprise-wide projects such as the Engineered Value Chain. The principal responsibility of the Data Scientist is to be an independent contributor to multi-person analytic teams. This position has a depth of knowledge in quantitative analytic methods, data management, and or associated digital technologies suitable to handle all but the most complex issues. This position is expected to be familiar with the company s processes, products, and organization, as well as its customers, competitors, and stakeholders. Work is typically directed by a direct supervisor, project or team lead through a review of results. Decisions on routine, medium risk issues that may affect the project team, suppliers or internal customers may be made by this position. Challenges include meeting expectations in delivering results, learning to refine solutions to better fit complex situations, making timely decisions, and communicating effectively with all project stakeholders. This position demonstrates thorough knowledge of statistical approaches, data management techniques, and/or related digital technologies, and the ability to handle complex issues. The incumbent demonstrates very good communication and presentation skills, being able to explain conclusions to customers who have limited knowledge and experience with quantitative analytical methods. As an individual contributor on teams, they should also exhibit strong initiative and teamwork skills, and a comprehensive knowledge of Caterpillar Inc., its products and services; its internal systems, processes, and procedures; and the external environment in which it competes. The responsibilities of the data scientist would involve design, develop, and deploying of predictive models and machine learning algorithms to support business decision-making. Lead data gathering, preprocessing, and transformation efforts from structured and unstructured sources. Collaborate with cross-functional teams to define analytical requirements and deliver insights through dashboards and reports. Develop and maintain scalable data pipelines using tools such as SQL, Snowflake, and Python. Apply Natural Language Processing (NLP), time-series analysis, and anomaly detection techniques to real-world datasets. Contribute to the development of internal Python packages and reusable analytics components What you will have Bachelor s degree, preferably in engineering, finance, statistics, economics, mathematics, or a similar field with quantitative coursework, and 4-5 years of professional experience utilizing quantitative analysis OR Master s degree and 2-3 years of experience OR PhD in one of the associated fields. Top Candidate Will Also Have: 2-4 years experience in manipulating data sets and building statistical models Ability to work on increasingly more complex assignments Strong problem-solving skills with an emphasis on product development. Knowledge of the statistical tools, processes, and practices to describe business results in measurable scales; ability to use statistical tools and processes to assist in making business decisions. Knowledge of principles, technologies and algorithms of machine learning (Supervised/unsupervised, clustering, decision tree learning, artificial neural networks, etc.); ability to develop, implement and deliver related systems, products and services. Experience using statistical computer languages (R, Python, SQL, etc.) to manipulate data and draw insights from large data sets Experience working with and creating data architectures Excellent written and verbal communication skills for coordinating across teams A drive to learn and master new technologies and techniques Experience using web services: AWS services, Snowflake, Spark Must be comfortable working in MS Office, and industry standard statistics and data visualization Packages - Power BI/Tableau Additional Information: This position requires the selected candidate to work Full -Time in the Whitefield Bangalore, Karnataka office. This position requires candidate to work a 5-day -a -week schedule in the office Domestic Relocation is available Less than 10% travel is expected Skills desired: Business Statistics: Knowledge of the statistical tools, processes, and practices to describe business results in measurable scales; ability to use statistical tools and processes to assist in making business decisions. Level Working Knowledge: Explains the basic decision process associated with specific statistics. Works with basic statistical functions on a spreadsheet or a calculator. Explains reasons for common statistical errors, misinterpretations, and misrepresentations. Describes characteristics of sample size, normal distributions, and standard deviation. Generates and interprets basic statistical data. Accuracy and Attention to Detail : Understanding the necessity and value of accuracy; ability to complete tasks with high levels of precision. Level Extensive Experience: Evaluates and makes contributions to best practices. Processes large quantities of detailed information with high levels of accuracy. Productively balances speed and accuracy. Employs techniques for motivating personnel to meet or exceed accuracy goals. Implements a variety of cross-checking approaches and mechanisms. Demonstrates expertise in quality assurance tools, techniques, and standards. Analytical Thinking : Knowledge of techniques and tools that promote effective analysis; ability to determine the root cause of organizational problems and create alternative solutions that resolve these problems. Level Working Knowledge: Approaches a situation or problem by defining the problem or issue and determining its significance. Makes a systematic comparison of two or more alternative solutions. Uses flow charts, Pareto charts, fish diagrams, etc. to disclose meaningful data patterns. Identifies the major forces, events and people impacting and impacted by the situation at hand. Uses logic and intuition to make inferences about the meaning of the data and arrive at conclusions. Machine Learning: Knowledge of principles, technologies and algorithms of machine learning; ability to develop, implement and deliver related systems, products and services. Level Working Knowledge: Completes specific tasks and initiatives utilizing machine learning technologies, such as search engine optimization. Utilizes specific tools and techniques to process descriptive and inferential statistics. Applies specific computing languages and tools in machine learning, such as R and Python. Explores to use machine learning in one own areas to make business improvements. Conducts data mining and cleaning initiatives. Programming Languages: Knowledge of basic concepts and capabilities of programming; ability to use tools, techniques and platforms in order to write and modify programming languages. Level Working Knowledge: Participates in the implementation and support of specialized programming languages. Conducts basic reviews on writing a specific programming language within a specific platform. Assists with the design and development of specialized programming languages. Follows an organization's standards, policies and guidelines for structured programming specifications. Diagnoses and reports minor or routine programming language problems. Query and Database Access Tools : Knowledge of data management systems; ability to use, support and access facilities for searching, extracting and formatting data for further use. Level Working Knowledge: Defines, creates and tests simple queries by using associated command language in a specific environment. Applies appropriate query tools used to connect to the data warehouse. Obtains and analyzes query access path information and query results. Employs tested query statements to retrieve, insert, update and delete information. Works with advanced features and functions including sorting, filtering and making simple calculations. Requirements Analysis: Knowledge of tools, methods, and techniques of requirement analysis; ability to elicit, analyze and record required business functionality and non-functionality requirements to ensure the success of a system or software development project. Level Working Knowledge: Follows policies, practices and standards for determining functional and informational requirements. Confirms deliverables associated with requirements analysis. Communicates with customers and users to elicit and gather client requirements. Participates in the preparation of detailed documentation and requirements. Utilizes specific organizational methods, tools and techniques for requirements analysis.\

Mandatory Skills - Gen-AI, Data Science, Python, RAG and Cloud (AWS/Azure) Secondary - (Any) - Machine Learning, Deep Learning, ChatGPT, Langchain, Prompt, vector stores, RAG, llama, Computer vision, Deep learning, Machine learning, OCR, Transformer, regression, forecasting, classification, hyper parameter tunning, MLOps. Requirement- More than 6 years of experience in Data Engineering, Data Science and AI / ML domain Excellent understanding of machine learning techniques and algorithms, such as GPTs, CNN, RNN, k-NN, Naive Bayes, SVM, Decision Forests, etc. Experience using business intelligence tools (e.g. Tableau, PowerBI) and data frameworks (e.g. Hadoop) Experience in Cloud native skills. Knowledge of SQL and Python; familiarity with Scala, Java or C++ is an asset Analytical mind and business acumen and Strong math skills (e.g. statistics, algebra) Experience with common data science toolkits, such as TensorFlow, KERAs, PyTorch, PANDAs, Microsoft CNTK, NumPy etc. Deep expertise in at least one of these is highly desirable. E xperience with NLP, NLG and Large Language Models like BERT, LLaMa, LaMDA, GPT, BLOOM, PaLM, DALL-E, etc. Great communication and presentation skills. Should have experience in working in a fast-paced team culture. Experience with AIML and Big Data technologies like AWS SageMaker, Azure Cognitive Services, Google Colab, Jupyter Notebook, Hadoop, PySpark, HIVE, AWS EMR etc. Interested candidates share your CV at himani.girnar@alikethoughts.com with below details Candidate's name- Email and Alternate Email ID- Contact and Alternate Contact no- Total exp- Relevant experience- Current Org- Notice period- CCTC- ECTC- Current Location- Preferred Location- Pancard No-

Location: Bangalore Responsibilities: Lead the execution of complex data science projects ensuring timely delivery and high- quality outcomes which enables business outcome. Identify new initiatives using emerging AI technologies and present them to Head/Lead of Data science. Build reusable AI components and assets and ensure their consumption in seamless manner by other data science projects/products. Collaborate effectively with other teams including Product, DB/DW and Applicatioon teams to ensure quick resolution of dependencies. Skills & Experience Required Strong knowledge and hands on experience with Agentic frameworks like Crew AI, Lang graph, Swarm AI etc. Good understanding of MCP (Model context protocol) Must have contributed significantly to development of at least 2 Gen AI project Must have worked with multiple Gen AI models including GPT, Claude, Qwen, Lama etc. Strong understanding of statistical concepts including probability, conditional probability, probability distribution, sampling, estimation, hypothesis testing etc. Deep understanding of ML models Knowledge of AutoML models like H2o and Pycaret and Deep learning models including MLP (Multi-layer perceptron), CNN, RNN, Self organizing maps (SOM), GAN (Generative Adversarial Networks), RBM (Restricted Boltzmann Machines) and LSTM (Long Short-Term Memory Networks) is preferable. Significant experience in SQL, Python, and Spark., Airflow Hands on experience with one of the MLOpS tools like ML flow (Open source preferred) Eligibility Bachelor /Master or Ph.D. in Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field.